Keep pulling the thread on Errol Gardner.
Errol Gardner identifies agentic AI as the technology with genuinely transformational potential, but notes the challenge of rebuilding how an organization operates at scale is still ahead.
Errol Gardner believes the consulting industry is shifting from an input-based model (hours worked) to an output-based model due to the productivity gains from AI.
Errol Gardner estimates that on a scale of 0 to 10, the adoption of agentic AI in the enterprise is currently at less than 1.
Errol Gardner predicts that governments will inevitably intervene through regulation, taxes, or peer pressure to disincentivize organizations from large-scale job displacement due to AI.
Errol Gardner believes there will undoubtedly be the growth of new agent-native companies that are faster, cheaper, and more productive than traditional industry leaders.
Errol Gardner states that the single biggest impediment to change in any organization is typically related to human factors, such as leaders, middle managers, or the general workforce.
According to Errol Gardner, there is significant anxiety in the workforce regarding the possibility of AI displacing jobs.
Errol Gardner asserts that machine learning is already used at scale in many organizations, is well-embedded in various industries, and is driving efficiency.
Errol Gardner believes that the use of private Large Language Models (LLMs) within corporate firewalls to leverage internal data is increasingly common but not as pervasive as some may think.
A significant operational issue for large corporations is preventing employees from moving corporate data into public, uncontrolled Large Language Models (LLMs).
Errol Gardner states that all major organizations will now implement guardrails to monitor and prevent employees from moving company data to external, uncontrolled platforms.
EY built a private Large Language Model (LLM) and populated it with the firm's internal knowledge and information to provide employees with controlled access.